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Record W4310107990 · doi:10.1182/blood-2022-160274

Mirages - REDS Explorer: An Online Portal for Longitudinal Metabolomics Data from the REDS-III RBC Omics Study

2022· article· en· W4310107990 on OpenAlexaff
Travis Nemkov, Kyle W. Bartsch, Mars Stone, Matthew D. Galbraith, Rachel Culp‐Hill, Joaquı́n M. Espinosa, Tamir Kanias, Steven Kleinman, Michael P. Busch, Philip L Norris, Angelo D’Alessandro

Bibliographic record

VenueBlood · 2022
Typearticle
Languageen
FieldMedicine
TopicNeonatal Health and Biochemistry
Canadian institutionsUniversity of VictoriaUniversity of British Columbia
Fundersnot available
KeywordsMetabolomicsOmicsBiologyMedicineBioinformatics

Abstract

fetched live from OpenAlex

Over one hundred million units of packed red blood cells (pRBCs) are stored and transfused annually around the world. Storage of pRBCs in the blood bank contributes to a series of biochemical and morphological changes in pRBCs, collectively referred to as the "storage lesion(s)", that ultimately impact RBC capacity to circulate in the bloodstream of recipients, carry and deliver oxygen. A growing body of studies has shown that the metabolism of pRBCs is affected by storage duration, processing strategies, as well as donor exposures ("exposome"). The latter include diet; consumption of alcohol, caffeinated beverages; smoking; and use of medications that do not result in donor deferral. Furthermore donor genetics (e.g., sex, ethnicity, G6PD status and many other genetic traits in RBC proteins) and other biological factors (e.g., age, body mass index [BMI]) impact pRBC storage and transfusion efficacy. Despite significant advances in the characterization of the storage lesion, most omics studies have been limited in scale to tens of pRBC units. These studies thus failed to grasp the extent to which donor biology, processing strategies or other factors (exposures) impact the metabolic age of stored units (as opposed to the chronological age - i.e., days elapsed since donation). As such, it remains unclear whether or to what extent the molecular make up of a unit correlates to its hemolytic propensity and post-transfusion efficacy. To bridge this gap, we leveraged the Recipient Epidemiology and Donor Evaluation Study-IV-Pediatric (REDS-IV-P), a research program aimed at improving blood donor safety and optimizing transfusion outcomes. Overall, 97% (13,403) of the whole blood donations provided by 13,758 donors age 18+ who provided informed consent at four different blood centers across the US were evaluable for hemolysis parameters, including spontaneous and stress (oxidative and osmotic) hemolysis analysis in ~42-day stored RBC derived from 8,502 whole blood donations. A total of 643 donors scoring in the 5th and 95th percentile for hemolysis parameters were invited to donate a second unit of pRBCs, which were assayed at storage days 10, 23 and 42 for hemolytic parameters and mass spectrometry-based high-throughput metabolomics. A pilot study was performed on 599 samples as part of the REDS-III RBC Omics project, while the whole recalled donor cohort was assayed as part of REDS-IV-P, for a total of serial 1,929 samples. As part of the MIRAGES project (Metabolic Investigation of Red blood cells, as a function of Aging, Genetics, Environment and Storage), we generated the REDS Explorer portal, for real time data processing and visualization. The portal not only serves as the largest online metabolomics data repository in transfusion medicine, but also affords data elaborations, including correlations to biological characteristics (donor sex, age, BMI, blood group, Rh status), processing strategies (additive solutions, blood center, irradiation) and functional readouts (ferritin levels, hemolytic parameters). The user can adjust for relevant covariates, select specific ranges for variables such as age, and filter based on donor sex, additive solution or storage duration - while choosing between the REDS III pilot data or the REDS-IV-P full recalled donor cohort. The portal generates publication quality figures for free, direct download. For example, here we show that L-citrulline is a previously unappreciated marker of blood donor age increasing in pRBCs as a function of donor age (Figure 1.A-B - q=3.84 e-24), with opposite trends observed for hydroxyisovaleryl-carnitine (q = 3.55 e-11 Figure 1.C). The latter was then identified as the top positive correlate to donor ferritin levels at the time of donation (q = 1.47 e-16 - Figure 1.D). The portal facilitates generation and investigation of new data-driven hypotheses, enabling the rapid dissemination and/or further mechanistic testing, thus maximizing the value of large-scale initiatives such as REDS-III/IV-P. The blood donor population as a window on the larger healthy population, high-throughput metabolomics applications in transfusion medicine, and the MIRAGES: REDS Explorer portal are directly relevant to advances in the fields of epidemiology and hematology. Figure 1 - Example of an output from the MIRAGES - REDS Explorer portal - based on donor age and ferritin levelsFigure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.200
Threshold uncertainty score0.550

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.141
GPT teacher head0.357
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2022
Admission routes1
Has abstractyes

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